Simplifying Backend Operations

Stop Burning Cash on DevOps Tools: 5 Essentials That Actually Make Your Startup Profitable 💰 Startups waste thousands on flashy tools that sound impressive but drain budgets before product market fit is even in sight. After building and optimizing stacks for early-stage companies, here’s the honest truth: simplicity wins, especially when every dollar counts. 5 Proven, Cost-Effective DevOps Essentials 1. GitHub Actions (Free) Replace pricey CI/CD platforms. Handles deployment, testing, and automation. Most startups enjoy a generous free tier. 2. Docker + Docker Compose (Free) No need for Kubernetes at the start. Easily manage multi-container setups locally and in production. Scale your setup only when you outgrow Compose. 3. DigitalOcean Droplets (From $4/month) AWS is overkill for 90% of startups. Simple, affordable, predictable billing. Spend time building, not deciphering cloud invoices. 4. Prometheus + Grafana (Free, Open Source) Enterprise-grade monitoring without the enterprise bill. Get real visibility into your stack for zero dollars. 5. Nginx (Free) Powerful reverse proxy, SSL, and basic load balancing, all in one lean tool. No need to pay for load balancers you already have one! 🔧 Real-World Stack: What I Use Right Now At the startup I currently work with as a Backend/DevOps lead, here’s the ultra-lean devops setup I am using: ☁️ Cloud: DigitalOcean Droplets (no billing surprises) ⚙️ Infra: Nginx for routing, SSL, and load balancing 🚀 Backend: FastAPI with background tasks (async email, etc.) 🔁 Backup: Cron jobs + bash scripts 🧪 Deployment: GitHub pull + systemd service restart (bash magic) No bloat. No unnecessary spending. Just real value and reliability at every step. Let’s Connect! If you’re building a startup and want: - Lean, scalable backend systems (Django/FastAPI expertise) - DevOps pipelines optimized to save cash and boost reliability - Infrastructure tailored to your actual stage (not “unicorn” fantasies) - Automation that makes your life easier I’d love to chat. Drop a DM or comment, let’s build something efficient together! 👇 What lean tools or tactics have saved your startup real money or headaches? Let's learn together. #DevOps #Startups #BackendEngineering #Django #FastAPI #Cloud #DigitalOcean #TechEfficiency #CostOptimization #LeanStartup

One delayed update. One task no one knew they were responsible for. That’s all it took to watch $30K slip through the cracks a few years ago. It's something most business owners don't realize. The Bigger Your Business Gets, the More Small Inefficiencies Turn Into Major Liabilities. A small delay in a small business is an inconvenience. A small delay in a fast-scaling business can cost millions. ___________________________________________ At first, it’s manageable. A few late invoices. A couple of missed emails. A process that takes longer than it should. Annoying? Yes. Business-ending? Not yet. But then growth kicks in. More clients, more revenue, more moving parts. And suddenly: → That clunky onboarding process is now losing you high-value clients. → A simple miscommunication turns into a five-figure mistake. → A slow decision-making loop means opportunities are passing you by. Small inefficiencies don’t stay small when your business scales. They multiply. They compound. They turn into liabilities. The funny thing I, you don’t feel them until it’s too late. Most people only fix their backend after they’ve lost money, clients, or momentum. ___________________________________________ The real move is to fix it before growth exposes it. • Build a central hub for operations • Document everything in plain English • Automate the repetition, delegate the rest • Create simple workflows anyone can follow • Map out your entire process, spot every leak Choose tools that scale with your team When your business runs well while it’s still small, it not only survives as it grows, it grows faster and easier. ___________________________________________ Repost if this made a difference PS: I share the juicy stuff in my comment section

I built a simple image upload API in .NET some time back, without scalability in mind. Nothing fancy—upload, resize, done. But the moment real traffic hit, everything started to fall apart. Thumbnail generation slowed to a crawl, memory usage spiked, and the system just couldn’t keep up. The biggest mistake? I’d bundled the image processing directly into my main production app. One container, doing everything. So, when the image load increased, the entire app got dragged down with it. User experience took a nosedive. I knew I had to rethink it. So I tore the whole thing apart and rebuilt it with a serverless-first mindset. Now, images upload directly to S3. That triggers an event to SQS. A .NET Lambda function picks up the message from the SQS Queue, resizes the image using ImageSharp, and writes the thumbnail back to S3. No servers to manage. No background jobs. Just clean, event-driven processing. Also, more importantly, my production app is safe! I’ve documented the entire solution in a detailed guide—covering everything from architecture and validation to performance tuning and production-grade improvements like deduplication, compression, and monitoring. Honestly, one of the most satisfying serverless projects I’ve worked on. If you're working with image-heavy applications and want a scalable backend, this will give you a solid foundation. Read the full article here: https://lnkd.in/gXtrZPCd Would love to hear how you'd extend this further.

We automated 60% of our back-office operations using AI agents. We saved $2M/year. Now we’re open-sourcing how. Why? Because traditional “automation” is broken. RPA scripts crack with the smallest change. One UI shift, and you’re back to square one. That’s why 50% of RPA projects fail quietly. We needed a system that adapts. Learns. Self-heals. So we built one. With real agentic AI. What changed? → Repetitive ops didn’t just disappear — they evolved → Agents now read data, act on it, and adjust in real-time → Every Slack ping, CRM task, and internal update — handled, end-to-end This isn't a slide deck or a blog. It’s the actual blueprint that runs our business. And we’re opening it up. Here’s what you’ll get: ▪️Full backend system map (how agents flow across infra) ▪️Security + DevOps stack (audited for enterprise) ▪️Real prompt templates, fallback logic, error flows ▪️Screenshots from our own playbooks + dashboards This is the stuff we charged $100K for. You’re getting it free. 👇 Want the blueprint? Comment “Ops” and I’ll send it to you. 🔁 Repost to help more teams automate the boring stuff. Follow Gaurav Bhattacharya for more no-fluff GTM + AI system drops.

When dealing with file uploads, a common approach is: Frontend → Backend (via HTTP request) → Backend uploads to S3 However, this adds unnecessary CPU and memory overhead on the backend, especially for large files. A better approach: - Frontend sends file metadata to the backend - Backend generates a pre-signed URL from S3 - Frontend directly uploads the file to S3 using the signed URL Benefits? - Reduces backend load (no heavy file processing) - Faster uploads with direct client-to-storage transfer - More scalable architecture Update: As many fellow LinkedIn members suggested: This approach is good for simple use-cases. In case you need to process files, add watermarks, resize them or perform security related tasks on file, you will need to keep backend in loop. Unless there is a way to do it on frontend without compromising the security risks. #CloudStorage #S3 #DigitalOcean #BackendOptimization #Scalability #SoftwareArchitecture #SystemDesign #Architecture